{"id":"https://openalex.org/W7153319489","doi":"https://doi.org/10.48550/arxiv.2604.08377","title":"SkillClaw: Let Skills Evolve Collectively with Agentic Evolver","display_name":"SkillClaw: Let Skills Evolve Collectively with Agentic Evolver","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7153319489","doi":"https://doi.org/10.48550/arxiv.2604.08377"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.08377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.08377","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133392578","display_name":"Ziyu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ma, Ziyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121250414","display_name":"Shidong Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Shidong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133388457","display_name":"Yuxiang Ji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Yuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133358272","display_name":"Xucong Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xucong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100615250","display_name":"Yong Wang","orcid":"https://orcid.org/0009-0004-8237-9487"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133375343","display_name":"Yiming Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124942498","display_name":"Tongwen Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tongwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133362036","display_name":"Xiangxiang Chu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chu, Xiangxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5133392578"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.11339999735355377,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.11339999735355377,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.09679999947547913,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07999999821186066,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6432999968528748},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5508000254631042},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.41920000314712524},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3197000026702881},{"id":"https://openalex.org/keywords/dreyfus-model-of-skill-acquisition","display_name":"Dreyfus model of skill acquisition","score":0.28290000557899475}],"concepts":[{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6432999968528748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6237999796867371},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5508000254631042},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5475999712944031},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.41920000314712524},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.35920000076293945},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31209999322891235},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C132758656","wikidata":"https://www.wikidata.org/wiki/Q5307365","display_name":"Dreyfus model of skill acquisition","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2752000093460083},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.257999986410141},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.08377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.08377","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08377","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7832404375076294,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"model":[2],"(LLM)":[3],"agents":[4],"such":[5,69],"as":[6,99],"OpenClaw":[7],"rely":[8],"on":[9,192],"reusable":[10],"skills":[11,18,137,146],"to":[12,67,130,163],"perform":[13],"complex":[14],"tasks,":[15],"yet":[16],"these":[17,78],"remain":[19],"largely":[20],"static":[21],"after":[22],"deployment.":[23],"As":[24],"a":[25,57,65,83,150],"result,":[26],"similar":[27],"workflows,":[28],"tool":[29],"usage":[30],"patterns,":[31],"and":[32,96,113,125,153,186,190,198],"failure":[33],"modes":[34],"are":[35,147],"repeatedly":[36],"rediscovered":[37],"across":[38,155],"users,":[39,156],"preventing":[40],"the":[41,100,131,203],"system":[42],"from":[43,49,171],"improving":[44,104],"with":[45,116,141],"experience.":[46],"While":[47],"interactions":[48,98],"different":[50],"users":[51],"provide":[52],"complementary":[53],"signals":[54],"about":[55],"when":[56],"skill":[58,74,87,132,179],"works":[59],"or":[60,138],"fails,":[61],"existing":[62,136],"systems":[63],"lack":[64],"mechanism":[66],"convert":[68],"heterogeneous":[70],"experiences":[71],"into":[72,128,177],"reliable":[73],"updates.":[75],"To":[76],"address":[77],"issues,":[79],"we":[80],"present":[81],"SkillClaw,":[82],"framework":[84],"for":[85,103],"collective":[86],"evolution":[88],"in":[89,149,160,207],"multi-user":[90,175],"agent":[91,209],"ecosystems,":[92],"which":[93,120],"treats":[94],"cross-user":[95,183],"over-time":[97],"primary":[101],"signal":[102],"skills.":[105],"SkillClaw":[106,181],"continuously":[107],"aggregates":[108],"trajectories":[109],"generated":[110],"during":[111],"use":[112],"processes":[114],"them":[115,127,140],"an":[117],"autonomous":[118],"evolver,":[119],"identifies":[121],"recurring":[122],"behavioral":[123],"patterns":[124],"translates":[126],"updates":[129],"set":[133],"by":[134],"refining":[135],"extending":[139],"new":[142],"capabilities.":[143],"The":[144],"resulting":[145],"maintained":[148],"shared":[151],"repository":[152],"synchronized":[154],"allowing":[157],"improvements":[158],"discovered":[159],"one":[161],"context":[162],"propagate":[164],"system-wide":[165],"while":[166],"requiring":[167],"no":[168],"additional":[169],"effort":[170],"users.":[172],"By":[173],"integrating":[174],"experience":[176],"ongoing":[178],"updates,":[180],"enables":[182],"knowledge":[184],"transfer":[185],"cumulative":[187],"capability":[188],"improvement,":[189],"experiments":[191],"WildClawBench":[193],"show":[194],"that":[195],"limited":[196],"interaction":[197],"feedback,":[199],"it":[200],"significantly":[201],"improves":[202],"performance":[204],"of":[205],"Qwen3-Max":[206],"real-world":[208],"scenarios.":[210]},"counts_by_year":[],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2026-04-11T00:00:00"}
